Role of ambient ammonia in particulate ammonium formation at a rural site in the North China Plain
- 1State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
- 2CMA Meteorological Observation Centre, Beijing 100081, China
- 3State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- 4University of Science and Technology Beijing, Beijing 100083, China
- 5Baotou Steel Group Mining Research Institute, Baotou 014010, China
- 6South China University of Technology, Guangzhou 510641, China
- 7Chinese Research Academy of Environmental Sciences, Beijing 100012, China
- 8Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China
- anow at: College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
Correspondence: Zhaoyang Meng (email@example.com)
The real-time measurements of NH3 and trace gases were conducted, in conjunction with semi-continuous measurements of water-soluble ions in PM2.5 at a rural site in the North China Plain (NCP) from May to September 2013 in order to better understand chemical characteristics of ammonia and the impact of secondary ammonium aerosols on formation in the NCP. Extremely high NH3 and NH concentrations were observed after a precipitation event within 7–10 days following urea application. Elevated NH3 levels coincided with elevated NH, indicating that NH3 likely influenced particulate ammonium mass. For the sampling period, the average conversion ∕ oxidation ratios for NH (NHR), SO (SOR), and NO (NOR) were estimated to be 0.30, 0.64, and 0.24, respectively. The increased NH3 concentrations, mainly from agricultural activities and regional transport, coincided with the prevailing meteorological conditions. The high NH3 level with NHR of about 0.30 indicates that the emission of NH3 in the NCP is much higher than needed for aerosol acid neutralisation, and NH3 plays an important role in the formation of secondary aerosols as a key neutraliser. The hourly data obtained were used to investigate gas–aerosol partitioning characteristics using the thermodynamic equilibrium model ISORROPIA-II. Modelled SO, NO, and NH3 values agree well with the measurements, while the modelled NH values largely underestimate the measurements. Our observation and modelling results indicate that strong acids in aerosol are completely neutralised. Additional NH exists in aerosol, probably a result of the presence of a substantial amount of oxalic and other diacids.
Ammonia (NH3) is a very important alkaline constituent in the atmosphere, plays an important role in atmospheric chemistry and is closely related to ecosystems. NH3 has both direct and indirect impacts on critical environmental issues, including regional fine particles, acid rain, and eutrophication (Roelle and Aneja, 2002; Krupa, 2003; Reche et al., 2015). In addition, NH3 is a key species for neutralising H2SO4 and HNO3 in the atmosphere and forming (NH4)2SO4, NH4HSO4, and NH4NO3 (Erisman and Schaap, 2004; Walker et al., 2004), which are major inorganic components of fine particulate matters and contribute to regional haze (Ye et al., 2011; Meng et al., 2014; Wei et al., 2015). Global ammonia emission has more than doubled since pre-industrial times, mainly because of agricultural intensification (Galloway et al., 2003). The total ammonia emission in China in 2006 was estimated to be 16.07 million tonnes (Mt) (Dong et al., 2010). Such high emission makes NH3 one of the key species related to atmospheric environmental problems. Some studies have indicated that reducing NH3 concentrations could be an effective method for alleviating secondary inorganic PM2.5 pollution in China (Cao et al., 2009; Park et al., 2014; Wang et al., 2015; Xu et al., 2017).
As global food production requirements increase, agriculture plays an increasingly important role in local, regional, and global air quality (Walker et al., 2006). The North China Plain (NCP) is a highly populated region with intensive agricultural production as well as heavy industry. The region has been affected by severe haze and photochemical pollution in recent years (Guo et al., 2010; Wang et al., 2010; Luo et al., 2013). Covering only 3.3 % of the national area, the NCP region provides 40 and 25 % of China's wheat and corn production. To sustain such high agricultural productivity, chemical fertilisers have been intensively applied. Less than 30 % efficiency in N application causes approximately 40 % N loss through various routes including the leaching of NO and emission of NH3, N2O, and N2 (Zhang et al., 2010). So far, only a few limited studies have paid attention to the impacts of NH3 on air pollution in the NCP region. According to some studies (Dong et al., 2010; Ianniello et al., 2010; Meng et al., 2011, 2015; Shen et al., 2011), the high NH3 emission intensities observed in the NCP have been caused by high fertiliser application rates and numerous intensive livestock farms. However, there were few simultaneous high-time-resolution measurements of NH3 and NH in PM2.5 that also investigated the role in fine particulate formation in China. These studies are necessary to improve our understanding of ammonia pollution on regional air quality and of the impact on formation of secondary ammonium aerosols in the NCP.
During May–September 2013, the intensive field measurements of NH3 and other trace gases, water-soluble ions in PM2.5, and meteorological parameters took place at a rural site in the NCP. In this article, we report the results on NH3, trace gases and major water-soluble ions in PM2.5. We discuss temporal variations in and diurnal patterns of NH3 and NH. We also show results from thermodynamic equilibrium simulations and compared them with observations.
2.1 Measurement site
The measurements were performed from May to September 2013 at Gucheng (39∘08′ N, 115∘40′ E, 15.2 m a.s.l.), a rural site in the NCP, which is an Integrated Ecological Meteorological Observation and Experiment Station of the Chinese Academy of Meteorological Sciences. In Fig. 1, the location of the site is shown on the NCP map with the NH3 emission distribution for the year 2012 from the multi-resolution emission inventory of China (http://meicmodel.org/index.html). The measurement site chosen is situated for monitoring regional background concentrations of air pollutants in the North China Plain and has good regional representativeness (Lin et al., 2009). The site is approximately 110 km southwest of Beijing, 130 km west of Tianjin, and 160 km northeast of Shijiazhuang city in Hebei Province. The site is surrounded by farms, dense villages/towns, and the transportation network in the NCP. The main crops in the area surrounding the site are wheat (winter and spring) and corn (summer and fall). The site is influenced by high NH3 emissions from fertiliser use and animal husbandry in the surrounding area. Being in the warm temperate zone, the site has a typical temperate continental monsoon climate. Precipitation occurs mainly between May and August.
2.2 Sampling and analysis
Ambient NH3 was measured using an ammonia analyser (DLT-100, Los Gatos Research, USA), which utilises a unique laser absorption technology called off-axis integrated cavity output spectroscopy. The analyser has a precision of 0.2 ppb at a 100 s average and a maximum drift of 0.2 ppb over 24 h. The response time of the analyser is less than 2 s (with an optional external N920 vacuum pump). During the campaign, NH3 data were recorded at a 100 s average. In principle, the NH3 analyser does not need external calibration because the measured fractional absorption of light at an ammonia resonant wavelength is an absolute measurement of the ammonia density in the cell (manual of economical ammonia analyser – benchtop model 908-0016, Los Gatos Research). However, we confirmed the good performance of the NH3 analyser using a reference gas mixture NH3 ∕ N2 (Air Liquide, USA) traceable to the US National Institute for Standards and Technology (NIST). The reference gas of NH3 (25.92 ppm with an accuracy of ±2 %) was diluted to different concentrations using zero air and supplied to the analyser, and a sequence with five points of different NH3 concentrations (including zero and the concentrations ranging from 45 to 180 ppb) were repeated for several times to check the performance of the analyser.
As shown in Fig. S1 in the Supplement, the analyser rapidly followed changes of the NH3 concentration, produced stable response under stabilised NH3 concentrations, and accurately repeated (within the uncertainty) the supplied NH3 concentrations. During the calibration, it took about 20 min for the instrument to show 90 % of the changes in the NH3 concentrations supplied through an aerosol filter and a PTFE tubing (4.8 mm ID, about 3 m). However, these time delays also contained the balance time needed for the calibration system. The lag caused by the tubing and analyser should be much smaller. The NH3 analyser contains an internal inlet aerosol filter, which was cleaned before our campaign. Nevertheless, some very fine particles can deposit on the mirrors of the integrated cavity output spectrometer (ICOS) cell, leading to a gradual decline in reflectivity. However, slight mirror contamination does not cause errors in NH3 measurements because the mirror reflectivity is continually monitored and the measurement is compensated for using the mirror ring-down time. Interferences to NH3 measurements can be from the sample inlets, for example, due to water condensation or adsorption–desorption effects (e.g. Schwab, 2008; Norman et al., 2009). Such interferences were not quantified but reduced as much as possible. PTFE tubing (4.8 mm ID), which is one of the well-suited materials for NH3 measurement (Norman et al., 2009), was used to induce ambient air. The length of the tubing was kept as short as possible (about 5 m) to limit the residence time to less than 3 s. The aerosol filter at the inlet was changed every 2 weeks. Water condensation was avoided. Nevertheless, we cannot exclude the influence from adsorption and desorption, which can also occur on dry surfaces. However, this influence should be small at our site, where the NH3 concentration is very high, and cause mainly a lag in the recorded NH3 concentration. As hourly averages are used in the work, this lag may not exert a significant influence on our results.
A set of commercial instruments from Thermo Environmental Instruments Inc. were used to measure O3 (TE 49C), NO/NO2/NOx (TE 42CTL), CO (TE 48C), and SO2 (TE 43CTL). All instruments were housed in an air-conditioned room in the observation building at the site. Two parallel inlet tubes (Teflon, 4.8 mm ID × 8 m length) were shared by the analysers. The height of the inlets was 1.8 m above the roof of the building and about 8 m above the ground. The inlet residence time was estimated to be less than 5 s (Lin et al., 2009). Zero and span checks were performed weekly on the analysers of these trace gases to identify possible analyser malfunctions and zero drifts. Multipoint calibrations of SO2, NOx, CO, and O3 analysers were performed on the instruments at approximately 1 month intervals. Measurement records were saved as 1 min averages. After the correction of data on the basis of the multipoint calibrations, hourly average data were calculated and used for the analysis.
An ambient ion monitor (AIM; URG 9000D series, USA) was deployed at the site to measure hourly concentrations of water-soluble inorganic components in PM2.5 during 15 June–11 August 2013. A detailed description of the performance evaluation of the AIM-IC system is reported by Han et al. (2016). Briefly, ambient air was introduced to the AIM with a 2 m Teflon-coated aluminum pipe and particles larger than 2.5 µm were removed by a cyclone at a flow rate of 3 L min−1. A liquid diffusion denuder was used to remove the interfering acidic and basic gases, in combination with a steam-jet aerosol collector followed by an aerosol sample collector, until the particles could be injected into the ion chromatograph (Hu et al., 2014). The detection limits of NH, SO, NO, and Cl− were 0.05, 0.04, 0.05, and 0.01 µg m−3, respectively. For the AIM, multipoint calibrations were performed weekly using calibration standard solutions. Acceptable linearity of ions was obtained with an R2 of ≥ 0.999. The flow rate of the AIM was checked weekly at the sample inlet with a certified flow metre. The flow rate of the AIM was kept at 3 L min−1 with a standard derivation of < 1 %. Hourly data were obtained for the concentrations of water-soluble inorganic ions in summer 2013.
Meteorological parameters were measured at the site. Air temperature and relative humidity (RH) were monitored using a humidity and temperature probe (HMP155, Vaisala, Finland); wind speed and direction were measured using an anemometer (ZQZ-TFD12, Jiangsu Radio Scientific Institute Co. Ltd., China); rainfall was measured using a tilting rain gauge (SL2-1, Tianjin Meteorological Instrument Factory, China). Global radiation observations were made at the site but showed a drift by the end of July 2013. Instead we use the photolysis rate jNO2 observed using a 2-pi-actinic-flux spectrograph (CCD type, Meteorologie Consult GmbH, Germany) to indicate the radiation condition for photochemistry. Hourly meteorological data were calculated from the in situ measurements and used in this paper. Planetary boundary layer height (PBLH) values at 14:00 BST (all times in Beijing standard time throughout the paper) were derived from the ERA-Interim data using the bulk Richardson number method (Guo et al., 2016; Miao et al., 2017).
2.3 Data analysis
2.3.1 Chemical conversions of species
Sulfate and nitrate oxidation ratios (SOR and NOR) are defined as the molar ratio of SO and NO in PM2.5 to the total oxidised S and N, respectively (Zhang et al., 2011).
Similarly, the conversion ratio of ammonium (NHR) is expressed in terms of the ratio of ammonium to total ammonia (NHx), which could be a measure of the extent of transformation from NH3 to NH in areas with major local NH3 sources (Hu et al., 2014).
2.3.2 Thermodynamic equilibrium
Thermodynamic gas–aerosol equilibrium characteristics during summer 2013 were examined using the ISORROPIA-II model (Fountoukis and Nenes, 2007; Fountoukis et al., 2009). ISORROPIA-II is a thermodynamic equilibrium model for inorganic gases and aerosols in the atmosphere (available at http://isorropia.eas.gatech.edu/index.php?title=Main_Page). The concentrations of the measured NH3 and water-soluble ions in PM2.5 were input into the model as total (gas + aerosol) concentrations, along with simultaneously measured relative humidity and temperature data. ISORROPIA-II was run in the forward mode with metastable aerosol-state salt precipitate once the aqueous phase became saturated with respect to salts, which often showed better performance than the stable-state solution (solid + liquid) and was commonly applied in previous pH predictions (Guo et al., 2015; Bougiatioti et al., 2016; Liu et al., 2017). In this study, the aerosol properties as acidity and the water content of the aerosol are needed to investigate the aerosol acidity characteristics and role of heterogeneous chemistry in nitrate formation. The pH of aerosol water was calculated using the following equation:
where H (µg m−3) is the ion concentration of the equilibrium particle hydronium and AWC (µg m−3) is the aerosol water content from the ISORROPIA-II simulation. The evaluation of the AWC prediction showed a good performance compared with observed particle water (Bian et al., 2014; Guo et al., 2015).
The statistical analysis of the comparison between observations and model predictions was performed by calculating normalised mean bias (NMB) and normalised mean error (NME):
where Mi and Oi are modelled and observed data, respectively. N is the number of data points.
2.3.3 Trajectory calculation
The 72 h backward trajectories were calculated using the HYSPLIT 4.9 model (http://www.arl.noaa.gov/ready/hysplit4.html). The trajectories terminated at the height of 100 m above the ground. The trajectory calculations were performed at four times (00:00, 06:00, 12:00, and 18:00 UTC) per day in summer 2013. Individual back trajectories were grouped into five clusters. The number of clusters is identified according to the changes in total spatial variance (TSV). Five is chosen as the final number of clusters considering optimum separation of trajectories (larger number of clusters) and simplicity of display (lower number of cluster). The corresponding concentrations of trace gases and water-soluble ions were averaged over the period of 3 h ahead and after the arrival time for each backward trajectory for further analysis.
3.1 Overview of concentration levels of measured species
During 15 May–25 September 2013, the average concentrations (ranges) of NH3, SO2, and NOx were 36.2 (0.1–862.9), 5.0 (0–86.8), and 15.4 (2.7–67.7) ppb, respectively. As listed in Table 1, the concentration of NH3 at the NCP rural site was lower than that reported at Asian and African urban sites such as Lahore (Pakistan; Biswas et al., 2008), Colonelganj (India; Behera and Sharma, 2010), and Cairo (Egypt; Hassan et al., 2013) but higher than those from other areas in China, Europe, and North America (Plessow et al., 2005; Yao et al., 2006; Lin et al., 2006; Walker et al., 2006; Hu et al., 2008; Meng et al., 2011, 2014; Shen et al., 2011; Schaap et al., 2011; Makkonen et al., 2012; Behera et al., 2013; Gong et al., 2013; Li et al., 2014). For example, the NH3 at the NCP rural site was higher than that found at the Shangdianzi regional background station in the NCP (Meng et al., 2011), Lin'an regional background station in the Yangtze River Delta (YRD) in eastern China (Meng et al., 2014), and the rural site in Beijing (Shen et al., 2011). The relatively high concentrations of NH3 observed in this study were attributed to agricultural activities involving fertiliser use, vegetation, livestock, and human excrement and waste disposal in the surrounding region.
According to an inventory study (Zhang et al., 2010), the total agricultural NH3–N emission in 2004 in the NCP was 3071 kt yr−1, accounting for 27 % of the total emissions in China with 1620 kt yr−1 of NH3–N emissions caused by fertiliser applications, which is the largest emission source in China, accounting for more than half of the total agricultural emissions. In recent years, there were a few publications about China's national and regional emission inventories of NH3 (e.g. Zhou et al., 2015; Xu et al., 2015, 2016; Kang et al., 2016). However, these inventories are based on bottom-up studies, subject to substantial uncertainties in spatial and temporal variations in NH3 emissions. Ground-based observations of NH3 have been sparse. Our measurements, together with others, can be used for validating and constraining models that use bottom-up inventories, and hence help to reveal potential bias in NH3 emission inventories.
The observed concentration of SO2 at the NCP rural site was markedly lower than that reported for the same period in 2006–2007 (Lin et al., 2009). Because of a series of emission reduction measures implemented in recent years, SO2 levels have decreased markedly in the NCP (Lin et al., 2011). The average concentration of NOx was higher than that at the Shangdianzi (Meng et al., 2011) and Lin'an (Meng et al., 2014) regional background stations in the NCP and YRD region of China, which might be due to emissions from agricultural activities and motor vehicle sources (Lei and Wuebbles, 2013; Liu et al., 2013) in the NCP, but it was lower than those at urban sites in India (Behera and Sharma, 2010) and Egypt (Hassan et al., 2013).
The average concentrations (ranges) of NH, SO, and NO in PM2.5 were 19.8 (1.07–340.6), 20.5 (3.30–116.9), and 11.3 (1.09–109.3) µg m−3, respectively, at the NCP rural site during 15 June–11 August 2013. The average concentration of NH in PM2.5 was higher than that observed at the rural or urban sites in the NCP (Meng et al., 2011), the YRD (Meng et al., 2014), Beijing (Shen et al., 2011), Guangzhou (Hu et al., 2008), and Hong Kong (Yao et al., 2006) in China, and is comparable to that at the urban site in India (Behera and Sharma, 2010). The average concentration of SO in PM2.5 was higher than that at rural sites in the NCP (Meng et al., 2011) and YRD (Meng et al., 2014) in China, but was lower than that observed at rural sites in Guangzhou (Hu et al., 2008) in China as well as urban sites in India (Behera and Sharma, 2010) and Egypt (Hassan et al., 2013). The average concentration of NO in PM2.5 was higher than that observed at the rural sites in the YRD and Guangzhou (Hu et al., 2008) in China and lower than that at urban sites in India (Behera and Sharma, 2010) and Pakistan (Biswas et al., 2008). The elevated NH3 and NH in PM2.5 concentrations at the NCP rural site demonstrate severe ammonia and fine particulate ammonium pollution in this area.
3.2 Ambient ammonia
3.2.1 Temporal variation in NH3
The time series of hourly averages of NH3 and other trace gases together with meteorological parameters during 15 May–25 September 2013 at Gucheng are shown in Fig. 2. NH3 concentrations varied considerably during the observation period, ranging from 0.1 to 862.9 ppb. The Gucheng station has 8.67 ha of farmland. The observation period was during the wheat harvest and corn planting and growing. Corn was sown and fertilised with about 600 kg of fertiliser per hectare in late June. On 20 July corn was additionally fertilised with 225 to 300 kg of urea per hectare. After this fertilisation, there was a rainy period. The NH3 concentration increased rapidly on the seventh day after the urea application on 20 July, peaking during the 27–30 July period (Fig. 2b). The highest hourly value of NH3 (862.9 ppb) was observed at 04:00 local time on 29 July 2013, with the second highest concentration observed at 06:00 on the same day. The extremely high NH3 concentrations were probably caused by intensified soil emissions after rainfall on 26 July, which enhanced the soil moisture. Precipitation and the resulting soil water dynamics are known to strongly affect urea hydrolysis and subsequent NH3 emissions (Reynold and Wolf, 1987; Aranibar et al., 2004). The general increase in NH3 emissions was observed when soils with a high moisture content began to dry because of increased diffusion (Burch and Fox, 1989). In addition, high temperatures in summer promote NH3 volatilisation from urea and ammonium dibasic phosphate applied to crops.
The monthly concentration of NH3 depends on its source and meteorological conditions. The monthly average values of NH3 were 28.4, 73.9, 26.4, and 13.5 ppb in June, July, August, and September 2013, respectively. In summer, high temperature promotes the emission of NH3 from natural and fertilised soils as well as vegetation. The concentration of NH3 in July was approximately 5 times higher than that in September, which was influenced by a higher temperature and increased emission rates of local agricultural NH3 sources in July.
SO2 and NOx are the main precursors of sulfate and nitrate aerosols, and O3 plays an important role in atmospheric chemistry because it acts as a source of OH radicals through photolysis. The maximum hourly average concentrations of SO2 and NOx were 86.8 ppb at 00:00 on 21 May and 67.7 ppb at 10:00 on 17 September, respectively. O3 monthly levels were high in June (44.3 ppb) and July (43.7 ppb), with a maximum hourly average value of 149.9 ppb at 15:00 on 25 July 2013.
In contrast to NH3, the highest monthly levels of SO2 (7.0 ppb) and CO (885 ppb) were observed in June, which could be due to the open burning of agricultural waste (straw, cornstalks, and other crops) after harvest in the surrounding area. Previous studies have shown that the burning of crop residue is a crucial source of trace gases such as NOx and CO in the NCP during summer (Meng et al., 2009; Lin et al., 2011). The obvious impact of biomass burning was observed during the 16–19 June 2013 period. As CO is mainly emitted from anthropogenic sources such as the burning of biomass, the elevated CO concentrations (2529 ppb at 22:00 on 16 and 2488 ppb at 22:00 on 17 June) were observed. During this pollution episode, the average concentrations of NH3, SO2, NOx, O3, and CO were 42.6, 7.69, 18.8, 44.0, and 1092 ppb, respectively, which were about 1.2–1.5 times higher than the average values for the whole study period. The monthly concentrations of SO2, NOx, and CO in July and August decreased compared to those in June. In addition to less influences from biomass burning, meteorological conditions were also in favour of lowering the concentrations of these gases. Figure S2 shows the monthly average diurnal variations in jNO2 and the time series of hourly rainfall during June–August 2013. As can be seen, the average jNO2 increased from June to August, indicating better conditions for photochemical reduction in July and August. There was also a slight increase in rainfall from June to August, which may promote removal of the pollutants. For the secondary pollutant O3, the highest concentration was observed in June. This is consistent with previous results from Gucheng (Lin et al., 2009) and should be related with the annual maximum of background O3 in the NCP, which occurs in June (Ding et al., 2008; Lin et al., 2008).
3.2.2 Diurnal variations in NH3
The average diurnal variations in NH3 from June to September 2013 are shown in Fig. 3. As indicated in Fig. 3a, NH3 concentration maxima and minima were observed during 08:00–13:00 and 19:00–23:00, respectively. As for July, NH3 concentrations showed a considerably more pronounced diurnal pattern with a maximum of 59.5 ppb at 08:00. The concentration of NH3 gradually increased during 00:00–03:00, remained relatively constant during 04:00–06:00, and then rapidly increased from 06:00 (beginning just after sunrise). After peaking at approximately 08:00, a decrease was observed until it reached the minimum of 29.8 ppb at 19:00.
The morning peak of NH3 was also observed elsewhere and could have resulted from emissions from fertilised soils and plant stomata, evaporation of dew, human sources, and mixing down of ammonia from the residual layer (Trebs et al., 2004; Norman et al., 2009; Bash et al., 2010; Ellis et al., 2011). Figure 3b reveals that the relative humidity (90–89 %) and temperature (21.5–22.1 ∘C) remained relatively constant before 06:00 but increased later in the morning. The increasing temperature can heat the Earth's surface and vegetation leaves and reduce the RH, potentially leading to evaporation of NH3 from soil and plants and volatilisation of ammonium aerosol (Trebs et al., 2004; Norman et al., 2009; Ellis et al., 2011), which may increase NH3 concentrations in the morning. When the emission was occurring into a shallow boundary layer, NH3 increase would be more prominent. In addition, the morning rise might also be due to the break-up of the nocturnal boundary layer. During the sampling period, the majority of peaks of ammonia over 50 ppb occurred at night, which were attributed to local emissions such as from agricultural activity, into a shallow nocturnal boundary layer. It was supposed by Ellis et al. (2011) that the downward mixing of air containing higher NH3 from the residual layer could lead to an increase in surface NH3 after the break-up of the nocturnal boundary layer.
From Fig. 3a, it can be seen that in July the NH3 level was the highest and peaked earliest. One reason for this might be the increased emissions of local agricultural NH3 sources in July compared with those in June, August, and September. On average, the level NH3 in July had a maximum night-time increase (20.0 ppb from 20:00 to 06:00), which is much large than those in June (5.2 ppb), August (9.9 ppb), and September (1.8 ppb). The early morning increase in NH3 in July started from a much higher level than in other months, resulting in the earliest NH3 peak in July.
The Gucheng site is an experiment station for agrometeorological studies. Corn is the main crop in the station area and nearly all the agricultural areas surrounding it. In accordance with the climate in the NCP, corn is planted around the middle of June and grows rapidly in July. Therefore, July is the key period for the application of nitrogen fertilisers like urea. As mentioned above, the urea application at the station on 20 July 2013 and a precipitation process afterwards caused huge NH3 spikes during the end of July (Fig. 2b). In addition, the highest night-time temperature in July (Fig. 3b) could promote the soil emission of NH3, and the relatively lower wind speed (Fig. 3b) and lower PBLH (Fig. S3) in July were in favour of the accumulation of NH3 in surface air.
In summary, ambient NH3 at Gucheng showed interesting diurnal cycles, which look significantly different in different summer months. We believe the interplay of some processes, such as emissions from agricultural sources, meteorological conditions (temperature, relativity humidity, wind speed, PBLH, etc.), and chemical conversion, are important in the determination of levels and diurnal patterns of NH3 at the site. Are all of these processes important in the morning variation in NH3 or not? How important are they? What makes the difference in the peaking time and concentration of NH3 in different months? These are questions to be answered in the future.
3.3 Ambient ammonium aerosol
Secondary inorganic aerosols form from gas-phase precursors, which are mostly from anthropogenic activities such as industrial, agricultural, and motor vehicle emissions. Therefore, the major precursors (NH3, SO2, and NOx) are responsible for the formation of particulate ammonium, sulfate, and nitrate.
The hourly NH concentrations during 15 June–11 August 2013 ranged from 1.07 to 340.6 µg m−3, with an average concentration of 19.8 µg m−3. The highest monthly level of NH appeared in July and the lowest level appeared in June 2013. Similar to NH3, the concentration of NH also increased sharply after urea fertilisation, with the highest value (340.6 µg m−3) observed at 09:00 on 28 July 2013. The temporal variations in NH basically coincided with SO and NO (discussed in Sect. 3.6), reflecting that NH largely originated from the neutralisation between NH3 and acidic species.
The highest hourly SO concentration (116.9 µg m−3) was observed at 10:00 on 9 July and the second highest value was 111.4 µg m−3 at 18:00 on 6 August 2013, with an average concentration of 20.5 ± 13.6 µg m−3. Despite the lower concentrations of SO2, higher SO concentrations in summer were attributed to the higher temperature, O3 concentration, and solar radiation, which increase photochemical activities, atmospheric oxidation, and conversion of SO2 to SO. The average concentration of NO in PM2.5 was 11.3 ± 9.1 µg m−3. The highest value of 109.3 µg m−3 was observed at 14:00 on 22 June 2013 at the highest RH (93 %) and AWC (910 µg m−3). The high RH conditions in summer might dissolve a significant fraction of HNO3 and NH3 in humid particles, therefore increasing the concentrations of NO and NH in the atmosphere (Krupa, 2003; Trebs et al., 2004; Ianniello et al., 2010). The high NO concentrations were also mostly associated with large AWC, which indicates the importance of heterogeneous hydrolysis in the production of nitrate (Pathak et al., 2009). Conversely, NH3 more efficiently in reacted with SO2 in summer to form (NH4)2SO4.
Figure 4 shows correlations of observed NH with the sum of observed SO, SONO, and SONOCl−. Although all the correlations are relatively high, the slopes of the regression lines are far from unity. This cannot be due to bias in measurements. The major ion balance shows a ratio of 1.05 : 1.0 for cation : anion. The slope is 0.56 when all three strong acids are considered, suggesting that the neutralisation of the strong acids explains 56 % of the observed NH. In other words, nearly 44 % of the observed NH was due to the presence of other acids in aerosol particles.
3.4 Results from thermodynamic equilibrium simulation
We have used the thermodynamic equilibrium model ISORROPIA-II to investigate gas–aerosol partitioning characteristics. The model outputs include equilibrium SO, NO, NH3, NH, H, HNO3, and AWC. As shown in Fig. 5, the modelled SO, NO, and NH3 are highly correlated with the corresponding measurements, with the slopes of regression lines being 0.99, 1.01, and 1.13 for SO, NO, and NH3, respectively. The correlation between modelled and observed NH is comparably poor but still significant (R2= 0.46, P < 0.01), with a slope of 0.45. The modelled SO and NO agree nearly perfectly with the measurements, while the modelled NH3 and NH show a slight overestimation and a large underestimation of the respective measurements. Considering the unbalance between observed NH and the sum of observed SO NO Cl− (see Fig. 4), we believe that other acids in aerosol particles are important in the conversion of NH3 to NH. These other acids may be oxalic acid and other dicarboxylic acids. Although we did not measure organic acids in aerosol, the presence of oxalic acid and other low-molecular-weight dicarboxylic acids in aerosols is often reported (e.g. Hsieh et al., 2007; Kawamura et al., 2010, 2013; Sauerwein and Chan, 2017). There is no doubt that there is a significant amount of dicarboxylic acid over the NCP particularly during summer (Kawamura et al., 2013). Therefore, it is highly possible that neutralising dicarboxylic acids in aerosol particles contributed significantly to the conversion of ammonia to ammonium. The presence of a significant amount of dicarboxylic acid can explain the substantial underestimate of NH and slight overestimate of NH3 by the model well as the model simulations did not include organics, which were not observed. The low slope (0.45) of the regression line for modelled and observed NH implies that organic diacids contributed at least half to the conversion of ammonia to ammonium. Since more NH existed in aerosol than was required for neutralising inorganic acids, the ISORROPIA model simulated higher equilibrium NH3 than observed, leading to an overestimate of NH3.
Comparisons between the measurements and the modelled values give a positive NMB for NH3 (26.9 %) and a negative NMB for SO (−0.5 %), NO (−12.5 %), and NH (−32.6 %). NME gives an estimation of overall discrepancy between measurement and model (Sudheer and Rengarajan, 2015). The NME values for the model–observation comparison of NH3, SO, NO, and NH are 31.6, 0.9, 14.8, and 45.8 %, respectively. These results indicate that the model simulated SO and NO well but over-predicted NH3 and under-predicted NH by around 30 %, mainly because of the neglect of organics. Therefore, organics should be observed and included in the model simulations in future studies to better investigate aerosol components and gas-to-aerosol conversion.
The average concentration of simulated HNO3 was 0.7 µg m−3, showing a maximum value of 7.41 µg m−3 at 11:00 on 19 June 2013. The average diurnal variations in HNO3 and H are shown in Fig. 6a. Typical high HNO3 concentrations during daytime and low values at night-time during the observation period are predicted by the model, which is consistent with other studies (Makkonen et al., 2012; Sudheer and Rengarajan, 2015). The diurnal cycle of H is predicted with the highest level around 17:00. The concentrations of NH3 were closely associated with H, and higher NH3 always corresponded to lower H (Liu et al., 2017). The pH value of aerosol water, estimated based on the simulated results using Eq. (4), are mostly in the range of 2.5–4.5. The fine particles were moderately acidic in summer, with an average pH value of 3.5. On average, pH is over 3.5 during night-time and below 3.5 during daytime (Fig. 6b). Under the medium acidic conditions and high NH3 concentrations, organic acid like diacids are able to react with ammonia to form ammonium. Because we used ISORROPIA-II for inorganic aerosol composition and no organic acid measurements are available, we cannot analyse the role of organic acids in detail, though the model performed quite well (Fig. S4).
3.5 Relationship between ammonia and ammonium aerosol
The gas-to-particle conversion between NH3 and NH has been reported to be strongly affected by temperature, RH, radiation conditions, the concentration of primary acid gas, and other factors. In this study, NH concentrations correlated significantly and positively with NH3, with a correlation coefficient of 0.78 and a slope of 1.48 (Fig. 7a, n= 915, P < 0.01), suggesting that NH3 played an important precursor role in NH in PM2.5 formation.
The ratio of NH3 to NHx (NH3+NH has been used to identify the source of NHx and the relative contribution of NH3 to NHx deposition (Lefer et al., 1999; Walker et al., 2004). A value higher than 0.5 signifies that NHx is mainly from local NH3 sources and that the dry deposition of NH3 dominates the NHx deposition. Robarge et al. (2002) reported that more than 70 % of NHx was in the form of NH3 at an agricultural site in the southeastern United States and concluded that given a larger deposition velocity of ammonia compared with that of ammonium, a considerable fraction of NHx could be deposited locally rather than be transported out of the region. According to hourly average concentrations, the ratio of NH3 ∕ NHx varied from 0.22 to 0.97, with a mean ratio of 0.69 ± 0.14, suggesting that NH3 remained predominantly in the gas phase rather than the aerosol phase in summer 2013 at Gucheng.
The diurnal changes in gaseous precursors and aerosol species are controlled by emission and deposition processes, horizontal and vertical transport, and gas–particle partitioning. To investigate gas–particle conversion further, diurnal variation in NHx is shown in Fig. 7b. Between 08:00 and 18:00, a decrease in NH3 would result in an increase in NH, which coincided with higher sulfate concentrations. The decrease in gas phase ammonia is likely the result of uptake onto aerosols to form (NH4)2SO4. The diurnal variability in NHx may be controlled by transport and vertical exchange. Between the hours of 08:00 and 18:00, NH3 decreased by 43 % while NHx decreased by 49 %, suggesting that NH3 remained predominantly in the gas phase. Between 19:00 and 07:00, NH3 increased by 42 % and NHx increased by 51 %, indicating that gas–particle partitioning contributes significantly to the decrease in gas-phase ammonia during this time.
3.5.1 Gas-to-particle conversion ratio of NH3
The SOR and NOR are defined in literature to investigate SO and NO formation and gas–particle transformation (Zhang et al., 2011). The average values of SOR and NOR were estimated to be 0.64 and 0.24 during the observation period at Gucheng, with SOR and NOR being higher than previous measurements (Zhou et al., 2009; Du et al., 2011; Zhang et al., 2011). Yao et al. (2002) pointed out an SOR lower than 0.10 under conditions of primary source emissions and higher than 0.10 when sulfate was mainly produced through the secondary transformation of SO2 oxidation. The value of SOR reached 0.70 in August 2013, which may be due to the enhanced atmospheric oxidant levels, sufficient ammonia for neutralisation, and higher RH in summer at Gucheng (Tang et al., 2016).
To gain further insight into the transformation of NH3 to NH, the conversion ratio of ammonium (NHR) was investigated. NHR is a measure of the extent of transformation from NH3 to NH in areas with significant local NH3 sources, although it encompasses both transport and local equilibrium, the latter dominating further downwind from the source. In this study, the average hourly values of NHR ranged from 0.03 to 0.77, with an average of 0.30 during summer 2013. The average NHR level in this study was higher than that observed at an urban site in Beijing (Meng et al., 2017), indicating that high NH3 concentrations resulting from agricultural activities had a marked influence on the formation of ammonium.
3.5.2 Diurnal patterns of NHR, SOR, and NOR
Figure 8 presents the diurnal patterns of NHR, SOR, NOR, gaseous precursors, major water-soluble ions, and meteorological factors. As a key species contributing to the oxidisation capacity of the atmosphere, O3 can promote HNO3 formation, affecting the conversion ratio of NH3. O3 exhibited low levels in the morning and enhanced levels in the late afternoon. The lower morning concentrations may be due to the depositional loss of O3 under stable atmospheric conditions in early morning hours, and the higher levels in the afternoon could be due to the photochemical production of O3. The NH concentration started to increase from morning, reaching the maximum value (16.1 µg m−3) at 18:00, with a diurnal difference of 3.7 µg m−3. This diurnal pattern may be due to a combination of high NH3 concentrations, the intense solar radiation at noon, and the high oxidisation capacity of the atmosphere in the afternoon. A clear diurnal cycle of NHR existed, with an amplitude of 0.10 and a peak of 0.35 at 18:00, which is consistent with the higher SOR and RH.
The SO2 concentration showed a maximum at 09:00, with a secondary peak at 22:00. The concentration of SO showed small peaks at 11:00, 14:00, and 18:00, respectively, but no strong diurnal variation. SOR displayed a diurnal cycle with the highest value of 0.74 observed at 05:00. It is noted that the SOR was lower during daytime when photochemical reaction is intense. A higher SOR during night-time suggests the importance of dark reactions. SO2 is highly soluble and can easily be absorbed by wet aerosol particles. The high RH at night may have promoted this process.
As for the diurnal cycle of NOx, a peak was observed at 06:00 when the mixing layer was stable, and a broad valley was observed in the daytime, reflecting the influences of a higher mixing layer and stronger photochemical conversion. During the night, NOx concentrations increased again, resulting in the second maximum at 23:00. NO concentrations did not show profound diurnal variations but instead showed slightly higher values during the night time, probably because of the hydrolysis of dinitrogen pentoxide (N2O5) and the condensation of HNO3 under relatively low temperatures. NOR displayed a diurnal pattern with a maximum of 0.28 at 10:00, which was likely related to photochemical reactions under the conditions of high O3 concentrations and jNO2 levels.
Night-time formation, aerosol uptake, and hydrolysis of N2O5 are highly uncertain as has been pointed out (e.g. Xue et al., 2014). The NOx concentration during night-time was higher than during daytime, while the NO level during night-time was only slightly higher than that during daytime. By assuming a high aerosol surface-to-mass ratio (33.7 m2 g−1; Okuda, 2013) and a high uptake coefficient (0.1; Seinfeld and Pandis, 2006), we estimate the night-time N2O5 under the conditions over our site to be in the range of about 3–10 ppb, corresponding to a HNO3 production rate of about 1–3 ppb h−1 (or 2.6–7.7 µg m−3). This rate of HNO3 production would cause an obvious night-time production of NH. Indeed, we can see increases in the NH concentration and NHR at night (Fig. 8). However, a more or less accurate estimate of the relative contribution of the night N2O5 chemistry to NH3 conversion needs to be made in the future.
3.6 A case study of a pollution period
On several days during the study period, very high NH3 and inorganic PM2.5 concentrations were observed. Here we make a case study of a pollution period during 7–11 August 2013. Data on gases, major aerosol ions, and some key meteorological parameters are presented in Fig. 9. Some calculated parameters during this period are given in Fig. S5. As shown in Figs. 9 and S5, there was a sharp increase in NOx during the night and early morning of 10 August, followed by an increase in NH3 (peak value of 64 ppb) at 03:00. In the meantime, a large peak of AWC occurred and gaseous HNO3 decreased to nearly zero (Fig. S5), suggesting rapid uptake of wet aerosol. This event caused the first largest peak of SO NO NH. After this event, NH3 rose again and reached an even higher peak (76.3 ppb) shortly before noon on 10 August. This peak of NH3 coincided with a valley of NOx, but the HNO3 level increase and pH value decrease were observed in parallel. A few hours later SO2 showed a large peak and the second largest peak of SO NO NH occurred. These data show that a high NH3 concentration was accompanied by a large increase in concentrations of SO, NO, and NH, which is consistent with the view that NH3 plays an important role in particulate matter mass formation and that gas–particle conversion occurred when NH3 was available, though SO partitions to the aerosol phase impact NH3 level less (Gong et al., 2013).
The secondary ion concentrations had similar temporal distributions with slow accumulation and relatively rapid clearing under favourable meteorological conditions. There was a good correlation between NH3 and NH, SO, and NO (R= 0.33, 0.27, and 0.49, respectively, with P < 0.01). However, there was also a situation in which high NH3 was not associated with high SO NO NH, as indicated by the data around noon of 8 August (Fig. 9). During this case, AWC was extremely low and RH was around 40 %. These conditions do not favour heterogeneous reactions.
During 7–11 August 2013, the relationships of the observed NH versus those of SO, the sum of SO and NO, and the sum of SO, NO, and Cl− are presented in Fig. 10. It is known that (NH4)2SO4 is preferentially formed and the least volatile, NH4NO3 is relatively volatile, and NH4Cl is the most volatile. NH is thought to be first associated with SO. Afterwards, the excess of NH is associated with nitrate and chloride (Meng et al., 2015). It is noted that the correlation of NH with the sum of SO and NO (R= 0.91, slope = 1.23, with P < 0.01) was closer to unity than that of NH with SO (R= 0.80, slope = 1.65, with P < 0.01), suggesting that both SO and NO were associated with NH. As shown in Fig. 10, sulfate and nitrate were almost completely neutralised with most of the data above the 1:1 line. A few scattered data below the 1:1 line may be caused by uncertainties in measurements. Little difference was found between the regression slopes of NH with the sum of SO and NO and the sum of SO, NO, and Cl− due to the very low amount of NH4Cl. In this study, the level of NH3 was high enough to neutralise both SO and NO and likely to help form (NH4)2SO4 and NH4NO3. In addition to these substances, it is likely that NH3 also reacted with oxalic acid and other dicarboxylic acid to form ammonium oxalate and other organic ammonium aerosols, as discussed above. Data in Fig. 10 seem to be distributed in two groups, with the one (Group 1) covering low to middle levels but exhibiting a larger slope and the other (Group 2) covering middle to high levels but exhibiting a smaller slope. Data in Group 2 were mainly from 10 August 2013 when high NH, SO, and NO values were observed (see Fig. 9). The difference in slope between the two groups might be caused by different fractions of organic diacids that are considered to convert more ammonia to ammonium. Although no measurements of organic diacids are available to prove this, the significant changes in fractions of organic and inorganic aerosol components are often observed during pollution episodes in China (e.g. Wang et al., 2016). Reduced impact from organic diacids may bring the correlation of NH with the sum of SO, NO, and Cl− closer to the 1:1 line.
3.7 Transport effects on local ammonia and ammonium
The Gucheng site is located in a densely populated rural area in the NCP, and it is influenced by local sources in the surrounding areas and by long-range transport of pollutants from the residential and industrial centres around it. Dependence of the concentrations of NH3 on wind direction at Gucheng is studied to get insight into the distribution of local emission sources around the monitoring site. As shown in Fig. 11, during the sampling period, the prevailing surface winds at Gucheng were northeasterly and southwesterly. High NH3 originated from the southwest sector of the measurement site, which may be due to a local unidentified agricultural or industrial source or transport from the Xushui township, which is approximately 15 km away from Gucheng. Lower NH3 concentrations were observed under winds from other sectors. Since NH3 is either readily converted to NH or subjected to dry deposition, high concentrations are found only close to the surface and near the emission sources. Previous studies have reported an inverse relationship between ground-level concentrations of trace gases, such as ammonia, and wind speed (Robarge et al., 2002; Lin et al., 2011; Meng et al., 2011). Thus, NH3 concentrations might be generally lower at higher wind speeds because of turbulent diffusion.
To identify the impact of long-range air transport on the surface air pollutant levels and secondary ions at Gucheng, the 72 h backward trajectories were calculated using the HYSPLIT 4.9 model.
As can be seen in Fig. 12, Clusters 1, 2, and 3 represent relatively low and slowly moving air parcels, with Cluster 2 coming from northwest areas at the lowest transport height among the five clusters. The air masses of Clusters 1 and 3 originate from the southeast of Gucheng. Clusters 4 and 5 represent air parcels mainly from the far northwest.
The trajectories in Cluster 2 came from the local areas around Gucheng, and it was the most important cluster to the Gucheng site, contributing 56 % to the air masses. Based on the statistics, the number of trajectories in Clusters 1, 2, and 3 account for 88 % of all the trajectories. As more than 80 % of air masses originating from or passing over the NCP region can influence the surface measurements at Gucheng, the observation results at Gucheng can represent the regional state of atmospheric components in the NCP region well.
Since the emission sources of pollutants are unevenly distributed in the areas surrounding the Gucheng site, air masses come from different directions and contain different levels of pollutants. The corresponding mean concentrations of NH3, SO2, NOx, NH, SO, and NO in PM2.5 in different clusters of backward trajectories are also included in Table 2 in order to characterise the dependence of the pollutant concentrations on air masses.
Large differences in the concentrations of NH3, SO2, NOx, NH, SO, and NO in PM2.5 existed among the different clusters, with cluster 2 corresponding to the highest NH3 concentration (48.9 ppb) and second highest NOx, NH, and SO concentrations (14.4 ppb and 17.5 and 22.1 µg m−3, respectively).
Cluster 1 corresponds to the highest SO2, NH, SO, and NO concentrations (7.9 ppb and 22.3, 22.6 and 17.7 µg m−3, respectively) and the second highest NH3 level (32.8 ppb). Cluster 3 had the highest NOx level (15.1 ppb), the second highest SO2 and NO levels (4.8 ppb and 11.8 µg m−3, respectively), and had the third highest concentrations of NH3, NH, and SO (28.5 ppb and 14.6 and 20.2 µg m−3, respectively).
Based on Table 2, the lowest NH3, SO2, NOx, NH, SO, and NO levels corresponded to Cluster 5, which was expected to bring cleaner air masses to the surface. As demonstrated by backward trajectories, more than half of the air masses during the sampling period from the NCP region contributed to the atmospheric NH3 variations, and both regional sources and long-distance transport from the southeast played important roles in the observed ammonium aerosol at the rural site in the NCP.
Online measurements of NH3, trace gases, and water-soluble ions in PM2.5 were conducted during May–September 2013 at a rural site in the NCP, where a large amount of ammonia was emitted because of agricultural activities. The average concentrations (ranges) of NH3 and NH in PM2.5 were 36.2 (0.1–862.9) ppb during 15 May–25 September 2013, and 19.8 (1.07–340.6) µg m−3 during 15 June–11 August 2013, respectively; these are considerably higher than those reported at other sites in China, Europe, and North America. Extremely high NH3 and NH concentrations were observed, which was attributed to a high soil moisture level due to rainfall on the days following the urea application. Elevated NH3 levels coincided with elevated NH, indicating the contribution of atmospheric NH3 to secondary inorganic aerosols during periods of agricultural activity. NH3 contributed 69 % to the total NH3+ NH in summer, suggesting that NHx remained predominantly in the gas phase rather than the aerosol phase in summer 2013 at Gucheng.
The average conversion ∕ oxidation ratios for NH (NHR), SO (SOR), and NO (NOR) were estimated to be 0.30, 0.64, and 0.24 in summer 2013, respectively. Results reveal that the concentrations of NH3, NH, and NHR had clear diurnal variations during the observation period. High NH3 and NH were observed during the late night and early morning periods. NHR also showed higher values at night, suggesting the importance of heterogeneous reactions driven by high night-time RH. The hourly data obtained were used to investigate gas–aerosol partitioning characteristics using the thermodynamic equilibrium model ISORROPIA-II. Modelled SO, NO, and NH3 values agree well with the measurements, while the modelled NH largely underestimates the measurements. Our measurement and modelling results indicate that the strong acids in aerosol particles over the rural site were neutralised well by NH3. Nearly half of the ammonium was not associated with strong acids but probably with oxalic acid and other diacids, which may present under the medium aerosol acidity (pH around 3.5).
The back trajectory analysis indicates that the transport from the NCP region contributed 56 % of the air mass with high NH3 levels. Meanwhile, long-distance transport from the southeast accounted for 32 % of the air mass with high NH, SO, and NO at the rural site in the NCP.
NH3 is currently not included in China's emission control policies of air pollution precursors, though people have been discussing the necessity of doing so for years. Our findings highlight the important role of NH3 in secondary inorganic and organic aerosol formation. As the emissions and concentration of NH3 in the NCP are much higher than needed for aerosol acid neutralisation, we speculate that a substantial amount of reduction in NH3 emission is required to see its effect on the alleviation of PM2.5 pollution in the NCP. Therefore, further strong reduction of the emissions of primary aerosol, NH3, SO2, NOx, and volatile organic compounds is suggested to address the serious occurrence of PM2.5 pollution on the NCP.
The data used in this study are available from the corresponding author upon request (firstname.lastname@example.org).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-18-167-2018-supplement.
The authors declare that they have no conflict of interest.
This work was supported by the National Natural Science Foundation of China
(21377165, 41330422, and 21777191), the China Special Fund for Meteorological
Research in the Public Interest (GYHY201206015), and the Environmental
Protection Public Welfare Scientific Research Project, Ministry of
Environmental Protection of the People's Republic of China (grant nos. 201509001, 201509002-04, and 201309009). The authors would like to thank
Xiangde Xu and Yu Song for their helpful support and suggestions.
The authors would like to thank Yaqiang Wang for providing NH3
emission data and Chao He for help with plotting the graphs.
Edited by: Eleanor Browne
Reviewed by: two anonymous referees
Aranibar, J. N., Otter, L., Macko, S. A., Feral, C. J. W., Epstein, H. E., Dowty, P. R., Eckardt, F., Shugart, H. H., and Swap, R. J.: Nitrogen cycling in the soil plant system along a precipitation gradient in the Kalahari sands, Glob. Change Biol., 10, 359–373, 2004.
Bash, J. O., Walker, J. T., Katul, G. G., Jones, M. R., Nemitz, E., and Robarg, W. P.: Estimation of In-Canopy Ammonia Sources and Sinks in a Fertilized Zea mays Field, Environ. Sci. Technol., 44, 1683–1689, 2010.
Behera, S. N. and Sharma, M.: Investigating the potential role of ammonia in ion chemistry of fine particulate matter formation for an urban environment, Sci. Total Environ., 408, 3569–3575, 2010.
Behera, S. N., Betha, R., and Balasubramanian, R.: Insight into chemical coupling among acidic gases, ammonia and secondary inorganic aerosols, Aerosol Air Qual. Res., 13, 1282–1296, 2013.
Bian, Y. X., Zhao, C. S., Ma, N., Chen, J., and Xu, W. Y.: A study of aerosol liquid water content based on hygroscopicity measurements at high relative humidity in the North China Plain, Atmos. Chem. Phys., 14, 6417–6426, https://doi.org/10.5194/acp-14-6417-2014, 2014.
Biswas, K. F., Ghauri, B. M., and Husain, L.: Gaseous and aerosol pollutants during fog and clear episodes in South Asian urban atmosphere, Atmos. Environ., 42, 7775–7785, 2008.
Bougiatioti, A., Bezantakos, S., Stavroulas, I., Kalivitis, N., Kokkalis, P., Biskos, G., Mihalopoulos, N., Papayannis, A., and Nenes, A.: Biomass-burning impact on CCN number, hygroscopicity and cloud formation during summertime in the eastern Mediterranean, Atmos. Chem. Phys., 16, 7389–7409, https://doi.org/10.5194/acp-16-7389-2016, 2016.
Burch, J. A. and Fox, R. H.: The effect of temperature and initial soil moisture content on the volatilization of ammonia from surface applied urea, Soil Sci., 147, 311–318, 1989.
Cao, J. J., Zhang, T., Chow, J. C., Watson, J. G., Wu, F., and Li, H.: Characterization of Atmospheric Ammonia over Xi'an, China, Aerosol Air Qual. Res., 9, 277–289, 2009.
Ding, A. J., Wang, T., Thouret, V., Cammas, J.-P., and Nédélec, P.: Tropospheric ozone climatology over Beijing: analysis of aircraft data from the MOZAIC program, Atmos. Chem. Phys., 8, 1–13, https://doi.org/10.5194/acp-8-1-2008, 2008.
Dong, W., Xing, J., and Wang, S.: Temporal and spatial distribution of anthropogenic ammonia emissions in China: 1994–2006, Environ. Sci., 31, 1457–1463, 2010 (in Chinese).
Du, H. H., Kong, L. D., Cheng, T. T., Chen, J. M., Du, J. F., Li, L., Xia, X. G., Leng, C. P., and Huang, G. H.: Insights into summertime haze pollution events over Shanghai based on online water soluble ionic composition of aerosols, Atmos. Environ., 45, 5131–5137, 2011.
Ellis, R. A., Murphy, J. G., Markovic, M. Z., VandenBoer, T. C., Makar, P. A., Brook, J., and Mihele, C.: The influence of gas-particle partitioning and surface-atmosphere exchange on ammonia during BAQS-Met, Atmos. Chem. Phys., 11, 133–145, https://doi.org/10.5194/acp-11-133-2011, 2011.
Erisman, J. W. and Schaap, M.: The need for ammonia abatement with respect to secondary PM reductions in Europe, Environ. Pollut., 129, 159–163, 2004.
Fountoukis, C. and Nenes, A.: ISORROPIA II: a computationally efficient thermodynamic equilibrium model for K+-Ca2+-Mg2+-NH-Na+-SO-NO-Cl−-H2O aerosols, Atmos. Chem. Phys., 7, 4639–4659, https://doi.org/10.5194/acp-7-4639-2007, 2007.
Fountoukis, C., Nenes, A., Sullivan, A., Weber, R., Van Reken, T., Fischer, M., Matias, E., Moya, M., Farmer, D., and Cohen, R. C.: Thermodynamic characterization of Mexico City aerosol during MILAGRO 2006, Atmos. Chem. Phys., 9, 2141–2156, https://doi.org/10.5194/acp-9-2141-2009, 2009.
Galloway, J. N., Aber, J. D., Erisman, J. W., Seitzinger, S. P., Howarth, R. W., Cowling, E. B., and Cosby, B. J.: The nitrogen cascade, BioScience, 53, 341–353, 2003.
Gong, L. W., Lewicki, R., Griffin, R. J., Tittel, F. K., Lonsdale, C. R., Stevens, R. G., Pierce, J. R., Malloy, Q. G. J., Travis, S. A., Bobmanuel, L. M., Lefer, B. L., and Flynn, J. H.: Role of atmospheric ammonia in particulate matter formation in Houston during summertime, Atmos. Environ., 77, 893–900, 2013.
Guo, H., Xu, L., Bougiatioti, A., Cerully, K. M., Capps, S. L., Hite Jr., J. R., Carlton, A. G., Lee, S.-H., Bergin, M. H., Ng, N. L., Nenes, A., and Weber, R. J.: Fine-particle water and pH in the southeastern United States, Atmos. Chem. Phys., 15, 5211–5228, https://doi.org/10.5194/acp-15-5211-2015, 2015.
Guo, J., Miao, Y., Zhang, Y., Liu, H., Li, Z., Zhang, W., He, J., Lou, M., Yan, Y., Bian, L., and Zhai, P.: The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data, Atmos. Chem. Phys., 16, 13309–13319, https://doi.org/10.5194/acp-16-13309-2016, 2016.
Guo, S., Hu, M., Wang, Z. B., Slanina, J., and Zhao, Y. L.: Size-resolved aerosol water-soluble ionic compositions in the summer of Beijing: implication of regional secondary formation, Atmos. Chem. Phys., 10, 947–959, https://doi.org/10.5194/acp-10-947-2010, 2010.
Han, B., Zhang, R., Yang, W., Bai, Z., Ma, Z., and Zhang, W.: Heavy haze episodes in Beijing during January 2013: inorganic ion chemistry and source analysis using highly time-resolved measurements from an urban site, Sci. Total Environ., 544, 319–329, 2016.
Hassan, S. K., El-Abssawy, A. A., and Khoder, M. I.: Characteristics of gas-phase nitric acid and ammonium-nitrate-sulfate aerosol, and their gas-phase precursors in a suburban area in Cairo, Egypt, Atmos. Pollut. Res., 4, 117–129, 2013.
Hsieh, L. Y., Kuo, S. C., Chen, C. L., and Tsai, Y. I.: Origin of low-molecular-weight dicarboxylic acids and their concentration and size distribution variation in suburban aerosol, Atmos. Environ., 41, 6648–6661, 2007.
Hu, G. Y., Zhang, Y. M., Sun, J. Y., Zhang, L. M., Shen, X. J., Lin, W. L., and Yang, Y.: Variability, formation and acidity of water-soluble ions in PM2.5, in Beijing based on the semi-continuous observations, Atmos. Res., 145–146, 1–11, 2014.
Hu, M., Wu, Z. J., Slanina, J., Lin, P., Liu, S., and Zeng, L. M.: Acidic gases, ammonia and water-soluble ions in PM2.5 at a coastal site in the Pearl River Delta, China, Atmos. Environ., 42, 6310–6320, 2008.
Ianniello, A., Spataro, F., Esposito, G., Allegrini, I., Rantica, E., Ancora, M. P., Hu, M., and Zhu, T.: Occurrence of gas phase ammonia in the area of Beijing (China), Atmos. Chem. Phys., 10, 9487–9503, https://doi.org/10.5194/acp-10-9487-2010, 2010.
Kang, Y., Liu, M., Song, Y., Huang, X., Yao, H., Cai, X., Zhang, H., Kang, L., Liu, X., Yan, X., He, H., Zhang, Q., Shao, M., and Zhu, T.: High-resolution ammonia emissions inventories in China from 1980 to 2012, Atmos. Chem. Phys., 16, 2043–2058, https://doi.org/10.5194/acp-16-2043-2016, 2016.
Kawamura, K., Barrie, L. A., and Desiree, T.-S.: Intercomparison of the measurements of oxalic acid in aerosols by gas chromatography and ion chromatography, Atmos. Environ., 44, 5316–5319, 2010.
Kawamura, K., Tachibana, E., Okuzawa, K., Aggarwal, S. G., Kanaya, Y., and Wang, Z. F.: High abundances of water-soluble dicarboxylic acids, ketocarboxylic acids and α-dicarbonyls in the mountaintop aerosols over the North China Plain during wheat burning season, Atmos. Chem. Phys., 13, 8285–8302, https://doi.org/10.5194/acp-13-8285-2013, 2013.
Krupa, S. V.: Effects of atmospheric ammonia (NH3) on terrestrial vegetation: A review, Environ. Pollut., 124, 179–221, 2003.
Lefer, B., Talbot, R., and Munger, J.: Nitric acid and ammonia at a rural northeastern US site, J. Geophys. Res., 104, 1645–1661, 1999.
Lei, H. and Wuebbles, D. J.: Chemical competition in nitrate and sulfate formations and its effect on air quality, Atmos. Environ., 80, 472–477, 2013.
Li, Y., Schwandner, F. M., Sewell, H. J., Zivkovich, A., Tigges, M., Raja, S., Holcomb, S., Molenar, J. V., Sherman, L., Archuleta, C., Lee, T., and Collett, J. L.: Observations of ammonia, nitric acid, and fine particles in a rural gas production region, Atmos. Environ., 83, 80–89, 2014.
Lin, W., Xu, X., Zhang, X., and Tang, J.: Contributions of pollutants from North China Plain to surface ozone at the Shangdianzi GAW Station, Atmos. Chem. Phys., 8, 5889–5898, https://doi.org/10.5194/acp-8-5889-2008, 2008.
Lin, W., Xu, X., and Zhang, X.: Characteristics of gaseous pollutants at Gucheng, a rural site southwest of Beijing, J. Geophys. Res., 114, D00G14, https://doi.org/10.1029/2008JD010339, 2009.
Lin, W., Xu, X., Ge, B., and Liu, X.: Gaseous pollutants in Beijing urban area during the heating period 2007–2008: variability, sources, meteorological, and chemical impacts, Atmos. Chem. Phys., 11, 8157–8170, https://doi.org/10.5194/acp-11-8157-2011, 2011.
Lin, Y. C., Cheng, M. T., Ting, W. Y., and Yeh, C. R.: Characteristics of gaseous HNO2, HNO3, NH3 and particulate ammonium nitrate in an urban city of central Taiwan, Atmos. Environ., 40, 4725–4733, 2006.
Liu, M., Song, Y., Zhou, T., Xu, Z., Yan, C., Zheng, M., Wu, Z., Hu, M., Wu, Y., and Zhu, T.: Fine particle pH during severe haze episodes in northern China, Geophys. Res. Lett., 44, https://doi.org/10.1002/2017GL073210, 2017.
Liu, X. J., Zhang, Y., Han, W.X., Tang, A. H., Shen, J. L., Cui, Z. L., Peter, V., Jan, W. E., Keith, G., Peter, C., Andreas, F., and Zhang, F. S.: Enhanced nitrogen deposition over China, Nature, 28, 459–463, 2013.
Luo, X. S., Liu, P., Tang, A. H., Liu, J. Y., Zong, X. Y., Zhang, Q., Kou, C. L., Zhang, L. J., Fowler, D., Fangmeier, A., Christie, P., Zhang, F. S., and Liu, X. J.: An evaluation of atmospheric Nr pollution and deposition in North China after the Beijing Olympics, Atmos. Environ., 74, 209–216, 2013.
Makkonen, U., Virkkula, A., Mäntykenttä, J., Hakola, H., Keronen, P., Vakkari, V., and Aalto, P. P.: Semi-continuous gas and inorganic aerosol measurements at a Finnish urban site: comparisons with filters, nitrogen in aerosol and gas phases, and aerosol acidity, Atmos. Chem. Phys., 12, 5617–5631, https://doi.org/10.5194/acp-12-5617-2012, 2012.
Meng, Z. Y., Xu, X. B., Yan, P., Ding, G. A., Tang, J., Lin, W. L., Xu, X. D., and Wang, S. F.: Characteristics of trace gaseous pollutants at a regional background station in Northern China, Atmos. Chem. Phys., 9, 927–936, https://doi.org/10.5194/acp-9-927-2009, 2009.
Meng, Z. Y., Lin, W. L., Jiang, X. M., Yan, P., Wang, Y., Zhang, Y. M., Jia, X. F., and Yu, X. L.: Characteristics of atmospheric ammonia over Beijing, China, Atmos. Chem. Phys., 11, 6139–6151, https://doi.org/10.5194/acp-11-6139-2011, 2011.
Meng, Z. Y., Zhang, R. J., Lin, W. L., Jia, X. F., Yu, X. M., Yu, X. L., and Wang, G. H.: Seasonal variation of ammonia and ammonium aerosol at a background station in the Yangtze River Delta Region, China, Aerosol Air Qual. Res., 3, 756–766, 2014.
Meng, Z. Y., Xie, Y. L., Jia, S. H., Zhang, R., Lin, W. L., Xu, X. B., and Yang, W.: The characteristics of atmospheric ammonia at Gucheng, a Rural Site in the North China Plain in summer 2013, J. Appl. Meteorol. Sci., 26, 141–150, 2015 (in Chinese).
Meng, Z. Y., Lin, W. L., Zhang, R. J., Han, Z. W., and Jia, X. F.: Summertime ambient ammonia and its effects on ammonium aerosol in urban Beijing, China, Sci. Total Environ., 579, 1521–1530, 2017.
Miao, Y., Guo, J., Liu, S., Liu, H., Li, Z., Zhang, W., and Zhai, P.: Classification of summertime synoptic patterns in Beijing and their associations with boundary layer structure affecting aerosol pollution, Atmos. Chem. Phys., 17, 3097–3110, https://doi.org/10.5194/acp-17-3097-2017, 2017.
Norman, M., Spirig, C., Wolff, V., Trebs, I., Flechard, C., Wisthaler, A., Schnitzhofer, R., Hansel, A., and Neftel, A.: Intercomparison of ammonia measurement techniques at an intensively managed grassland site (Oensingen, Switzerland), Atmos. Chem. Phys., 9, 2635–2645, https://doi.org/10.5194/acp-9-2635-2009, 2009.
Okuda, T.: Measurement of the specific surface area and particle size distribution of atmospheric aerosol reference materials, Atmos. Environ., 75, 1–5, 2013.
Park, R. S., Lee, S., Shin, S.-K., and Song, C. H.: Contribution of ammonium nitrate to aerosol optical depth and direct radiative forcing by aerosols over East Asia, Atmos. Chem. Phys., 14, 2185–2201, https://doi.org/10.5194/acp-14-2185-2014, 2014.
Pathak, R. K., Wu, W. S., and Wang, T.: Summertime PM2.5 ionic species in four major cities of China: nitrate formation in an ammonia-deficient atmosphere, Atmos. Chem. Phys., 9, 1711–1722, https://doi.org/10.5194/acp-9-1711-2009, 2009.
Plessow, K., Spindler, G., Zimmermann, F., and Matschullat, J.: Seasonal variations and interactions of N-containing gases and particles over a coniferous forest, Saxony, Germany, Atmos. Environ., 39, 6995–7007, 2005.
Reche, C., Viana, M., Karanasiou, A., Cusack, M., Alastuey, A., Artiñano, B., Revuelta, M., López-Mahía, P., Blanco-Heras, G., Rodríguez, S., Sánchez de la Campa, A., Fernández- Camacho, R., González-Castanedo, Y., Mantilla, E., Tang, S., and Querol, X.: Urban NH3 levels and sources in six major Spanish cities, Chemosphere, 119, 769–777, 2015.
Reynold, C. M. and Wolf, D.: Effect of soil moisture and air relative humidity on ammonia volatilization from surface-applied urea, Soil Sci., 143, 144–152, 1987.
Robarge, W. P., Walker, J. T., McCulloch, R. B., and Murray, G.: Atmospheric concentrations of ammonia and ammonium at an agricultural site in the southeast United States, Atmos. Environ., 36, 16611–1674, 2002.
Roelle, P. A. and Aneja, V. P.: Characterization of ammonia emissions from soils in the upper coastal plain, North Carolina, Atmos. Environ., 36, 1087–1097, 2002.
Sauerwein, M. and Chan, C. K.: Heterogeneous uptake of ammonia and dimethylamine into sulfuric and oxalic acid particles, Atmos. Chem. Phys., 17, 6323–6339, https://doi.org/10.5194/acp-17-6323-2017, 2017.
Schaap, M., Otjes, R. P., and Weijers, E. P.: Illustrating the benefit of using hourly monitoring data on secondary inorganic aerosol and its precursors for model evaluation, Atmos. Chem. Phys., 11, 11041–11053, https://doi.org/10.5194/acp-11-11041-2011, 2011.
Schwab, J. J.: Ambient Gaseous Ammonia: Evaluation of Continuous Measurement Methods Suitable for Routine Deployment, Final Report Prepared for the New York State Energy Research and Development Authority (NYSERDA)-Final Report 08-15, New York, October, 2008.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics: from air pollution to climate change, 2nd Edn., Wiley Interscience, New Jersey, 2006.
Shen, J. L., Liu, X. J., Zhang, Y., Fangmeier, A., Goulding, K., and Zhang, F. S.: Atmospheric ammonia and particulate ammonium from agricultural sources in the North China Plain, Atmos. Environ., 45, 5033–5041, 2011.
Sudheer, A. K. and Rengarajan, R.: Time-resolved inorganic chemical composition of fine aerosol and associated precursor gases over an urban environment in western India: gas-aerosol equilibrium characteristics, Atmos. Environ., 109, 217–227, 2015.
Tang, X., Zhang, X. S., Ci, Z. J., Guo, J., and Wang, J. Q.: Speciation of the major inorganic salts in atmospheric aerosols of Beijing, China: Measurements and comparison with model, Atmos. Environ., 133, 123–134, 2016.
Trebs, I., Meixner, F. X., Slanina, J., Otjes, R., Jongejan, P., and Andreae, M. O.: Real-time measurements of ammonia, acidic trace gases and water-soluble inorganic aerosol species at a rural site in the Amazon Basin, Atmos. Chem. Phys., 4, 967–987, https://doi.org/10.5194/acp-4-967-2004, 2004.
Walker, J. T., Whitall, D. R., Robarge, W., and Paerl, H. W.: Ambient ammonia and ammonium aerosol across a region of variable ammonia emission density, Atmos. Environ., 38, 1235–1246, 2004.
Walker, J. T., Robarge, W. P., Shendrikar, A., and Kimball, H.: Inorganic PM2.5 at a U.S. agricultural site, Environ. Pollut., 139, 258–271, 2006.
Wang, G., Zhang, R., Gomez, M. E., Yang, L., Zamora, M. L., Hu, M., Lin, Y., Peng, J., Guo, S., Meng, J., Li, J., Cheng, C., Hua, T., Ren, Y., Wang, Y., Gao, J., Cao, J., An, Z., Zhou, W., Li, G., Wang, J., Tian, P., Marrero-Ortiz, W., Secrest, J., Du, Z., Zheng, J., Shang, D., Zeng, L., Shao, M., Wang, W., Huang, Y., Wang, Y., Zhu, Y., Li, Y., Hu, J., Pan, B., Cai, L., Cheng, Y., Ji, Y., Zhang, F., Rosenfeld, D., Liss, P. S., Duce, R. B., Kolb, C. E, and Molina, M. J.: Persistent sulfate formation from London Fog to Chinese haze, P. Natl. Acad. Sci. USA, 113, 13630–13635, 2016.
Wang, S. S., Nan, J. L., Shi, C. Z., Fu, Q. Y., Gao, S., Wang, D. F., Cui, H. X., Alfonso, S. L., and Zhou, B.: Atmospheric ammonia and its impacts on regional air quality over the megacity of Shanghai, China. Sci. Rep., 5, 15842, https://doi.org/10.1038/srep15842, 2015.
Wang, T., Nie, W., Gao, J., Xue, L. K., Gao, X. M., Wang, X. F., Qiu, J., Poon, C. N., Meinardi, S., Blake, D., Wang, S. L., Ding, A. J., Chai, F. H., Zhang, Q. Z., and Wang, W. X.: Air quality during the 2008 Beijing Olympics: secondary pollutants and regional impact, Atmos. Chem. Phys., 10, 7603–7615, https://doi.org/10.5194/acp-10-7603-2010, 2010.
Wei, L. F., Duan, J. C., Tan, J. H., Ma, Y. L., He, K. B., Wang, S. X., Huang, X. F., and Zhang, Y. X.: Gas-to-particle conversion of atmospheric ammonia and sampling artifacts of ammonia in spring of Beijing, Sci. China Earth Sci., 58, 345–355, 2015.
Xu, P., Zhang, Y., Gong, W., Hou, X., Kroeze, C., Gao, W., and Luan, S.: An inventory of the emission of ammonia from agricultural fertilizer application in China for 2010 and its high-resolution spatial distribution, Atmos. Environ., 115, 141–148, 2015.
Xu, P., Liao, Y. J., Lin, Y. H., Zhao, C. X., Yan, C. H., Cao, M. N., Wang, G. S., and Luan, S. J.: High-resolution inventory of ammonia emissions from agricultural fertilizer in China from 1978 to 2008, Atmos. Chem. Phys., 16, 1207–1218, https://doi.org/10.5194/acp-16-1207-2016, 2016.
Xu, W., Song, W., Zhang, Y., Liu, X., Zhang, L., Zhao, Y., Liu, D., Tang, A., Yang, D., Wang, D., Wen, Z., Pan, Y., Fowler, D., Collett Jr., J. L., Erisman, J. W., Goulding, K., Li, Y., and Zhang, F.: Air quality improvement in a megacity: implications from 2015 Beijing Parade Blue pollution control actions, Atmos. Chem. Phys., 17, 31–46, https://doi.org/10.5194/acp-17-31-2017, 2017.
Xue, L. K., Wang, T., Gao, J., Ding, A. J., Zhou, X. H., Blake, D. R., Wang, X. F., Saunders, S. M., Fan, S. J., Zuo, H. C., Zhang, Q. Z., and Wang, W. X.: Ground-level ozone in four Chinese cities: precursors, regional transport and heterogeneous processes, Atmos. Chem. Phys., 14, 13175–13188, https://doi.org/10.5194/acp-14-13175-2014, 2014.
Yao, X. H., Chak, K. C., Fang, M., Cadle, S., Chan, T., Mulawa, P., He, K. B., and Ye, B. M.: The water-soluble ionic composition of PM2.5 in Shanghai and Beijing, China, Atmos. Environ., 36, 4223–4234, 2002.
Yao, X. H., Ling, T. Y., Fang, M., and Chan, C. K.: Comparison of thermodynamic predictions for in situ pH in PM2.5, Atmos. Environ. 40, 2835–2844, 2006.
Ye, X. N., Ma, Z., Zhang, J.C., Du, H. H., Chen, J. M., Chen, H., Yang, X., Gao, W., and Geng, F. H.: Important role of ammonia on haze formation in Shanghai, Environ. Res. Lett., 6, 024019, https://doi.org/10.1088/1748-9326/6/2/024019, 2011.
Zhang, T., Cao, J., Tie, X., Shen, Z., Liu, S., Ding, H., Han, Y., Wang, G., Ho, K., Qiang, J., and Li, W.: Water-soluble ions in atmospheric aerosols measured in Xi'an, China: Seasonal variations and sources, Atmos. Res., 102, 110–119, 2011.
Zhang, Y., Dore, A. J., Ma, L., Liu, X. J., Ma, W. Q., Cape, J. N., and Zhang, F. S.: Agricultural ammonia emissions inventory and spatial distribution in the North China Plain, Environ. Pollut., 158, 490–501, 2010.
Zhou, Y., Wang, T., Gao, X. M., Xue, L. K., Wang, X. F., Wang, Z., Gao, J., Zhang, Q. Z., and Wang, W. X.: Continuous observations of water-soluble ions in PM2.5 at Mount Tai (1534 m a.s.l.) in central-eastern China, J. Atmos. Chem., 64, 107–127, 2009.
Zhou, Y., Cheng, S., Lang, J., Chen, D., Zhao, B., Liu, C., Xu, R., and Li, T.: A comprehensive ammonia emission inventory with high-resolution and its evaluation in the Beijing-Tianjin-Hebei (BTH) region, China, Atmos. Environ., 106, 305–317, 2015.